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Wire and Arc Additive Manufacture (WAAM), the twist of wire during a robot's movement can result in the sudden changes of the wire feeding position and thus cause deposition defects and dimensional errors. In the worst case it may cause wire jamming and damage of the wire feeding system. Therefore on-line monitoring and correction of the wire deflection are very important for WAAM. In this paper, a vision based measuring method is proposed for detecting the deviations of the wire feeding position of a plasma welding based WAAM process. It uses adaptive threshold and Hough transform to extract the wire edges, judges and merges the coincident lines and applies Radon transform to measure the wire deflection. Software to automatically detect the wire deviation was developed based on the proposed method. The method and the software was verified with validation experiments.

Conceptions of acute public health events typically assume that they are tackled exclusively or principally through technical and medical solutions. Yet health and politics are inexorably linked. To better understand this link, this paper adopts a disaster diplomacy perspective for analysing and assessing the impacts of acute public health events on diplomatic outcomes. Two gaps in understanding disaster-health-politics connections are addressed: (i) how health interventions can impact diplomatic endeavours, especially for (ii) acute public health events. Three diverse case studies are interpreted from a disaster diplomacy perspective: Cuba's medical diplomacy, China and Severe Acute Respiratory Syndrome (SARS), and polio vaccination. Disaster diplomacy permits deeper investigation and analysis of connections amongst health, disaster, and diplomatic activities by viewing efforts on acute public health events as being political through disaster risk reduction (beforehand) and disaster response (during and afterwards). Understanding improves how health interventions affect diplomacy and on disaster diplomacy's limitations.

Image matting is an important problem in computer vision with significant theoretical interest and diverse practical applications, including image/video editing, target tracking, and object recognition. Pixel-pair-optimization-based image matting approaches have been shown very successful in estimating the opacity of the foreground by searching for the best pair of foreground and background pixels for each unknown pixel. However, extant approaches encounter difficulties in adapting to the changes of available computing resources, which limits the application of image matting. This drawback has motivated the present study, as a part of which a multi-scale evolutionary pixel pair optimization framework named pyramid matting framework (PMF) was developed. In this framework, the large-scale pixel pair optimization problem is transformed to multiple pixel pair optimization problems of different scales using image pyramid. The resulting problems are solved level by level, starting from the problem at the small scale. Pixel pair heuristic information obtained from solving low-scale problems are iteratively propagated to the spatially-related pixel pairs in the larger-scale problem. PMF can adapt to changes in available computing resources due to its capability of transforming a small-scale problem solution to the large-scale problem solution through the heuristic information propagation. Experimental results show that the PMF-based image matting approach not only provides high-quality alpha mattes with sufficient computing resources, but also works well when computing resources are scarce.